User centric noise source ranking

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

User centric noise source ranking is proposed as an extension to the conventional machinery noise ranking methodology. It focuses on the improvement of the machinery operator and additional personnel working conditions. Similar to the conventional noise ranking methodology, the partial noise sources are identified and their joint effect is evaluated. In the user centric noise ranking, the location where the combined noise effect is evaluated is the user or operator position. The operator may be inside a cabin, or directly exposed to the noise. Additionally, the noise data is analysed with psychoacoustic methods to obtain the noise annoyance for the experienced noise. This approach has been evaluated with acquired data from hard rock mining equipment working in real conditions. The analysis shows that the user centric noise source ranking methodology will expand the conventional noise ranking possibilities, because it allows analysis that is more detailed. As an additional requirements, user centric noise source ranking also limits the used component analysis methods and ways to acquire the noise data, and some signal source separation methods do not work properly. Psychoacoustic analysis methods employed require acquisition of sound pressure as a time series, and this limits the available algorithms. This creates new demands for the data acquisition and analysis methods, but the possible benefits will outweigh them.
Original languageEnglish
Title of host publicationEuronoise 2018 - Conference Proceedings
Pages869-876
Publication statusPublished - 2018
MoE publication typeNot Eligible
Event11th European Congress and Exposition on Noise Control Engineering, Euronoise 2018 - Heraklion, Greece
Duration: 27 May 201831 May 2018

Publication series

NameEuronoise
PublisherEuropean Acoustics Association EAA
ISSN (Print)2226-5147

Conference

Conference11th European Congress and Exposition on Noise Control Engineering, Euronoise 2018
CountryGreece
CityHeraklion
Period27/05/1831/05/18

Fingerprint

Mining equipment
Source separation
Acoustic noise
Machinery
Time series
Data acquisition
Rocks
Acoustic waves
Personnel

Keywords

  • Noise
  • cabin noise
  • psychoacoustics
  • source ranking
  • user centric

Cite this

Antila, M., Lamula, L., Kataja, J., Isomoisio, H., & Rantala, S. (2018). User centric noise source ranking. In Euronoise 2018 - Conference Proceedings (pp. 869-876). (Euronoise).
Antila, Marko ; Lamula, Lasse ; Kataja, Jari ; Isomoisio, Heikki ; Rantala, Seppo. / User centric noise source ranking. Euronoise 2018 - Conference Proceedings. 2018. pp. 869-876 (Euronoise).
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abstract = "User centric noise source ranking is proposed as an extension to the conventional machinery noise ranking methodology. It focuses on the improvement of the machinery operator and additional personnel working conditions. Similar to the conventional noise ranking methodology, the partial noise sources are identified and their joint effect is evaluated. In the user centric noise ranking, the location where the combined noise effect is evaluated is the user or operator position. The operator may be inside a cabin, or directly exposed to the noise. Additionally, the noise data is analysed with psychoacoustic methods to obtain the noise annoyance for the experienced noise. This approach has been evaluated with acquired data from hard rock mining equipment working in real conditions. The analysis shows that the user centric noise source ranking methodology will expand the conventional noise ranking possibilities, because it allows analysis that is more detailed. As an additional requirements, user centric noise source ranking also limits the used component analysis methods and ways to acquire the noise data, and some signal source separation methods do not work properly. Psychoacoustic analysis methods employed require acquisition of sound pressure as a time series, and this limits the available algorithms. This creates new demands for the data acquisition and analysis methods, but the possible benefits will outweigh them.",
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Antila, M, Lamula, L, Kataja, J, Isomoisio, H & Rantala, S 2018, User centric noise source ranking. in Euronoise 2018 - Conference Proceedings. Euronoise, pp. 869-876, 11th European Congress and Exposition on Noise Control Engineering, Euronoise 2018, Heraklion, Greece, 27/05/18.

User centric noise source ranking. / Antila, Marko (Corresponding author); Lamula, Lasse; Kataja, Jari; Isomoisio, Heikki; Rantala, Seppo.

Euronoise 2018 - Conference Proceedings. 2018. p. 869-876 (Euronoise).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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AU - Lamula, Lasse

AU - Kataja, Jari

AU - Isomoisio, Heikki

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N2 - User centric noise source ranking is proposed as an extension to the conventional machinery noise ranking methodology. It focuses on the improvement of the machinery operator and additional personnel working conditions. Similar to the conventional noise ranking methodology, the partial noise sources are identified and their joint effect is evaluated. In the user centric noise ranking, the location where the combined noise effect is evaluated is the user or operator position. The operator may be inside a cabin, or directly exposed to the noise. Additionally, the noise data is analysed with psychoacoustic methods to obtain the noise annoyance for the experienced noise. This approach has been evaluated with acquired data from hard rock mining equipment working in real conditions. The analysis shows that the user centric noise source ranking methodology will expand the conventional noise ranking possibilities, because it allows analysis that is more detailed. As an additional requirements, user centric noise source ranking also limits the used component analysis methods and ways to acquire the noise data, and some signal source separation methods do not work properly. Psychoacoustic analysis methods employed require acquisition of sound pressure as a time series, and this limits the available algorithms. This creates new demands for the data acquisition and analysis methods, but the possible benefits will outweigh them.

AB - User centric noise source ranking is proposed as an extension to the conventional machinery noise ranking methodology. It focuses on the improvement of the machinery operator and additional personnel working conditions. Similar to the conventional noise ranking methodology, the partial noise sources are identified and their joint effect is evaluated. In the user centric noise ranking, the location where the combined noise effect is evaluated is the user or operator position. The operator may be inside a cabin, or directly exposed to the noise. Additionally, the noise data is analysed with psychoacoustic methods to obtain the noise annoyance for the experienced noise. This approach has been evaluated with acquired data from hard rock mining equipment working in real conditions. The analysis shows that the user centric noise source ranking methodology will expand the conventional noise ranking possibilities, because it allows analysis that is more detailed. As an additional requirements, user centric noise source ranking also limits the used component analysis methods and ways to acquire the noise data, and some signal source separation methods do not work properly. Psychoacoustic analysis methods employed require acquisition of sound pressure as a time series, and this limits the available algorithms. This creates new demands for the data acquisition and analysis methods, but the possible benefits will outweigh them.

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Antila M, Lamula L, Kataja J, Isomoisio H, Rantala S. User centric noise source ranking. In Euronoise 2018 - Conference Proceedings. 2018. p. 869-876. (Euronoise).